Multidimensional Analysis of HBIM Segmentation
A Roadmap Towards Standardization
Bibliographic Data
| ID | 19489797 |
|---|---|
| Authors | Demitrios Galanakis (0000-0003-2082-0551, Hellenic Mediterranean University), Emmanuel Maravelakis (0000-0002-3193-9446, Hellenic Mediterranean University, corresponding author), Nectarios Vidakis (0000-0002-6100-932X, Hellenic Mediterranean University), Markos Petousis (0000-0003-1312-7898, Hellenic Mediterranean University), Antonios Konstantaras (0000-0002-1052-1948, Hellenic Mediterranean University), Massimiliano Pepe (0000-0003-2508-5066, University of Chieti-Pescara) |
| Year | 2026 |
| Volume | 9 |
| Issue | 6 |
| Pages | 232 |
| Publication date | 2026-06-12 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Heritage (JOURNAL) |
| Journal identifiers | ISSN: 2571-9408 • E-ISSN: 2571-9408 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/heritage9060232 |
| OpenAlex | W7164829088 |
| Language | EN |
| References cited | 95 |
This paper presents a multidimensional analysis of Historic Building Information Modeling (HBIM) segmentation, offering a roadmap towards standardization, a key dimension towards broader adoption within the Cultural Heritage (CH) sector. HBIM faces multiple challenges related to the lack of standardized protocols and varying definitions of Level of Detail (LOD) across applications. Amid the advancements of the fourth industrial revolution, integrating Building Information Modeling (BIM) improves sustainability and digital governance, aligning with the sustainable development agenda. Despite increasing academic interest, the implementation of HBIM remains limited, primarily due to the complexities and heterogeneities inherent in CH artifacts. This study begins with a purely qualitative strategy. Then, it introduces multidimensional and hierarchical clustering analysis to classify the unique characteristics of various HBIM applications such as segmentation, input, and data-capturing media. At the same time, it is a tool for fine-tuning keyword-based selection criteria, which is crucial in systematic or semi-systematic surveys in HBIM segmentation. The thematic analysis output is interrupted just before the conceptualization step, and theme extraction is diverted to correspondence analysis implemented in R, an open-source statistical package. Among the key findings of this paper is the classification of four distinct HBIM application clusters, revealing how specific workflows align with data acquisition methods, input formats, and Level of Detail (LOD) requirements. The analysis exposes critical standardization bottlenecks hindering wider-scale industry adoption, highlighting that challenges are domain-specific. Strong evidence shows that 3D modeling has not reached the required maturity level, with persisting challenges distributed non-uniformly within the applications spectrum. Finally, AI-driven automation relates with poor LOD outcome
Conceptualization · Dimension (graph theory) · Key (lock) · Multidimensional analysis · Online analytical processing · Qualitative analysis · Standardization · Workflow · 3D Modeling in Geospatial Applications · 3D Surveying and Cultural Heritage · BIM and Construction Integration
Preferred Reporting Items for Systematic Reviews and Meta-Analyses
Historic building information modelling (HBIM)
Literature review as a research methodology
Content analysis and thematic analysis
Automatic Threat Detection for Historic Buildings in Dark Places Based on the Modified OptD Method
Parametric Processes for the Implementation of HBIM—Visual Programming Language for the Digitisation of the Index of Masonry Quality
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Modelling and Stability Assessment of the Rock Cliffs and Xrobb l-Ġħaġin Neolithic Structure in Malta
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A Scan-to-BIM Approach for the Management of Two Arab-Norman Churches in Palermo (Italy)
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HBIM and BEM association
Semi-automatic classification of digital heritage on the Aïoli open source 2D/3D annotation platform via machine learning and deep learning
SVD-based point cloud 3D stone by stone segmentation for cultural heritage structural analysis - The case of the Apollo Temple at Delphi
Deep learning-based damage detection and segmentation in the battledore of Darbhanga Fort
An artificial neural network framework for classifying the style of cypriot hybrid examples of built heritage in 3D
Methodology for an HBIM workflow focused on the representation of construction systems of built heritage
A Step-by-Step Process of Thematic Analysis to Develop a Conceptual Model in Qualitative Research
| Citation velocity | historical |
|---|---|
| Highly cited | No |